Objective To explore the risk factors for UGIB after dual antiplatelet therapy(aspirin+P2Y12 receptor antagonist)in elderly patients with acute coronary syndrome(ACS)undergoing PCI,and then construct a nomogram model.Methods A total of 1590 elderly patients diagnosed with ACS and then undergoing PCI in Jinzhou Central Hospital from January 2019 to June 2022 were retrospectively recruited,and randomly divided into a testing group(n=1114)and a valida-tion group(n=476)in a ratio of 7∶3.Univariate and multivariate logistic regression analyses were applied to identify the independent risk factors for UGIB events,and then a prediction model was constructed and verified for its diagnostic performance.The predictive value of our prediction model for UGIB events was compared with that of PRECISE-DAPT scoring system.Results There were no statistical differences in baseline data between the testing group and the validation group(P＞0.05).The incidence of UGIB was 3.9％(62/1590)in the patients.Multivariate logistic regression analysis indicated that age(OR=1.064,95％CI:1.032-1.097,P=0.000),alcohol(OR=2.433,95％CI:1.220-4.823,P=0.011),heart failure(OR=3.734,95％CI:1.882-7.404,P=0.000),gastrointestinal ulcer/bleeding(OR=3.030,95％CI:1.391-6.618,P=0.005),and Cr(OR=1.017,95％CI:1.014-1.040,P=0.000)were independent risk factors for UGIB in these patients after dual antiplatelet therapy.The constructed nomogram model based on the risk factors obtained an AUC value of 0.806(95％CI:0.739-0.872)in the testing set and 0.838(95％CI:0.737-0.945)in the validation set.The AUC value of the PRECISE-DAPT scoring system in predicting UGIB was 0.674(95％CI:0.583-0.766),which was significantly lower than our mod-el(P＜0.05),indicating the nonogram showing good discriminability.Calibration curve analysis and H-L goodness of fit test revealed that our model had good consistency and was well fit(vali-dation set:P=0.846,testing set:P=0.326).Decision curve analysis displayed that our model showed good potential clinical benefits.Conclusion Age,history of gastrointestinal ulcer/bleed-ing,alcohol,heart failure and Cr are independent risk factors for UGIB in these post-PCI patients after dual antiplatelet therapy.The prediction model constructed with these factors has good dis-criminability,calibration and fitting,shows sound clinical application,and can be served as an ef-fective prediction tool for UGIB events in the patients.

Objective To explore the risk factors for UGIB after dual antiplatelet therapy(aspirin+P2Y12 receptor antagonist)in elderly patients with acute coronary syndrome(ACS)undergoing PCI,and then construct a nomogram model.Methods A total of 1590 elderly patients diagnosed with ACS and then undergoing PCI in Jinzhou Central Hospital from January 2019 to June 2022 were retrospectively recruited,and randomly divided into a testing group(n=1114)and a valida-tion group(n=476)in a ratio of 7∶3.Univariate and multivariate logistic regression analyses were applied to identify the independent risk factors for UGIB events,and then a prediction model was constructed and verified for its diagnostic performance.The predictive value of our prediction model for UGIB events was compared with that of PRECISE-DAPT scoring system.Results There were no statistical differences in baseline data between the testing group and the validation group(P＞0.05).The incidence of UGIB was 3.9％(62/1590)in the patients.Multivariate logistic regression analysis indicated that age(OR=1.064,95％CI:1.032-1.097,P=0.000),alcohol(OR=2.433,95％CI:1.220-4.823,P=0.011),heart failure(OR=3.734,95％CI:1.882-7.404,P=0.000),gastrointestinal ulcer/bleeding(OR=3.030,95％CI:1.391-6.618,P=0.005),and Cr(OR=1.017,95％CI:1.014-1.040,P=0.000)were independent risk factors for UGIB in these patients after dual antiplatelet therapy.The constructed nomogram model based on the risk factors obtained an AUC value of 0.806(95％CI:0.739-0.872)in the testing set and 0.838(95％CI:0.737-0.945)in the validation set.The AUC value of the PRECISE-DAPT scoring system in predicting UGIB was 0.674(95％CI:0.583-0.766),which was significantly lower than our mod-el(P＜0.05),indicating the nonogram showing good discriminability.Calibration curve analysis and H-L goodness of fit test revealed that our model had good consistency and was well fit(vali-dation set:P=0.846,testing set:P=0.326).Decision curve analysis displayed that our model showed good potential clinical benefits.Conclusion Age,history of gastrointestinal ulcer/bleed-ing,alcohol,heart failure and Cr are independent risk factors for UGIB in these post-PCI patients after dual antiplatelet therapy.The prediction model constructed with these factors has good dis-criminability,calibration and fitting,shows sound clinical application,and can be served as an ef-fective prediction tool for UGIB events in the patients.